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Introduction 📌

1 Introduction

Some weeks ago, in Utrecht, I had a fascinating discussion with my new friend Daniella from distant beautiful Peru. The discussion was around if Greece is really in such a poor economic spot. Since other Greeks and I probably told her many times that immigration is not always a choice but more of a necessity to find a good life quality, work-life balance, and mostly, opportunities that you can chase with your skills and strength. Even though she knew a lot concerning Greece, I feel like many others; she was still under the impression that despite the difficulties, Greece is still a European country. Thus, it should have some prosperous conditions for its young population to have a career and draw their future. And I do not blame her, as coming from Southern America who, from my knowledge, have their own economic situations, I would probably have the same questions. So I hope that exploring these data will shed some light on our exciting conversation.

Is it time for Greeks to return home and brain-drain turn to brain-gain? I will try to explore some data so at the end anyone can make up his own conclusions.

Notes 📝

I will use data from the OECD organization. The Organization for Economic Co-operation and Development (OECD) is a unique forum where the governments of 37 democracies with market-based economies collaborate to develop policy standards to promote sustainable economic growth.

All the Countries - members that are included in the OECD data are: Australia, Austria, Belgium, Canada, Chile, Colombia, Czechia, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, South Korea, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, Slovakia, Spain, Sweden, Switzerland, Turkey, United Kingdom, United States, Chile, Estonia, Israel, Slovenia, Latvia, Lithuania, Colombia, Costa Rica and the indexes OECD, G-7, EA19, EU27_2020.

For the purpose of this analysis, I will use data only from Countries within the European Union as most Greek immigrants etc., are located and working in other European Countries and not at least so much in Costa Rica or Mexico, for example. United Kingdom, USA, Canada, and Australia will also be included as there are a lot of Greeks located and working in these countries.

The Countries that will be included for the analysis and the graphs will be the following: Austria, Belgium, Czech Republic (Czechia), Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Spain, Sweden, Switzerland, United Kingdom, United States, Canada and Australia.

OECD Data Categories 📊

2 Overview

2.1 Unemployment

Unemployment 📉

The 5 (five) different data sets from OECD that I am gonna use to illustrate unemployment metrics, are the following together with their description (citation provided on references): Unemployment Rate , Unemployment Rate by Age Group , Unemployment Rates by Education Level , Long-term Unemployment Rate and Youth Unemployment Rate

📌 Unemployment rate : The unemployed are people of working age who are without work, are available for work, and have taken specific steps to find work. The uniform application of this definition results in estimates of unemployment rates that are more internationally comparable than estimates based on national definitions of unemployment. This indicator is measured in numbers of unemployed people as a percentage of the labour force and it is seasonally adjusted. The labour force is defined as the total number of unemployed people plus those in employment. Data are based on labour force surveys (LFS). For European Union countries where monthly LFS information is not available, the monthly unemployed figures are estimated by Eurostat.

📌 Unemployment rate by age group : The unemployed are people of working age who are without work, are available for work, and have taken specific steps to find work. The uniform application of this definition results in estimates of unemployment rates that are more internationally comparable than estimates based on national definitions of unemployment. Unemployment rates are shown for two age groups: people aged 15 to 24 (those just entering the labour market following education); and people aged 25 and over. This indicator is measured in numbers of unemployed people as a percentage of the labour force and it is seasonally adjusted. The labour force is defined as the total number of unemployed people plus those in civilian employment. Data are based on labour force surveys (LFS). For European Union countries where monthly LFS information is not available, the monthly unemployed figures are estimated by Eurostat.

📌 Unemployment rates by education level : This indicator shows the unemployment rates of people according to their education levels: below upper secondary, upper secondary non-tertiary, or tertiary. The unemployed are defined as people without work but actively seeking employment and currently available to start work. This indicator measures the percentage of unemployed 25-64 year-olds among 25-64 year-olds in the labour force.

📌 Long-term unemployment rate : Long-term unemployment refers to people who have been unemployed for 12 months or more. The long-term unemployment rate shows the proportion of these long-term unemployed among all unemployed. Unemployment is usually measured by national labour force surveys and refers to people reporting that they have worked in gainful employment for less than one hour in the previous week, who are available for work and who have sought employment in the past four weeks. Long-term unemployment causes significant mental and material stress for those affected and their families. It is also of particular concern for policy makers, as high rates of long-term unemployment indicate that labour markets are operating inefficiently. This indicator is measured as a percentage of unemployed.

📌 Youth unemployment rate : The youth unemployment rate is the number of unemployed 15-24 year-olds expressed as a percentage of the youth labour force. Unemployed people are those who report that they are without work, that they are available for work and that they have taken active steps to find work in the last four weeks.

Return to the tabbed sections to see more by clicking here 👉 Overview!

Return to the tabbed sections to see more by clicking here 👉 Overview!

2.2 Employment

Employment 💼

The 5 (five) different data sets from OECD that I am gonna use to illustrate employment metrics are the following together with their description (citation provided on references): Employment Rate , Employment Rate by Age Group , Employment Rate by Education Level , Self-employment Rate and Hours Worked

📌 Employment rate : Employment rates are defined as a measure of the extent to which available labour resources (people available to work) are being used. They are calculated as the ratio of the employed to the working age population. Employment rates are sensitive to the economic cycle, but in the longer term they are significantly affected by governments’ higher education and income support policies and by policies that facilitate employment of women and disadvantaged groups. Employed people are those aged 15 or over who report that they have worked in gainful employment for at least one hour in the previous week or who had a job but were absent from work during the reference week. The working age population refers to people aged 15 to 64. This indicator is seasonally adjusted and it is measured in terms of thousand persons aged 15 and over; and in numbers of employed persons aged 15 to 64 as a percentage of working age population.

📌 Employment rate by age group : The employment rate for a given age group is measured as the number of employed people of a given age as a percentage of the total number of people in that same age group. Employed people are defined as those aged 15 and over who report that they have worked in gainful employment for at least one hour in the previous week or who had a job but were absent from work during the reference week while having a formal job attachment. Employment rates are shown for four age groups: people aged 15-64 (the working age population): people aged 15 to 24 (those just entering the labour market following education); people aged 25 to 54 (those in their prime working lives); people aged 55 to 64 (those passing the peak of their career and approaching retirement). This indicator is seasonally adjusted and it is measured as a percentage in same age group.

📌 Employment by education level : This indicator shows the employment rates of people according to their education levels: below upper secondary, upper secondary non-tertiary, or tertiary. The employment rate refers to the number of persons in employment as a percentage of the population of working age. The employed are defined as those who work for pay or profit for at least one hour a week, or who have a job but are temporarily not at work due to illness, leave or industrial action. This indicator measures the percentage of employed 25-64 year-olds among all 25-64 year-olds.

📌 Self-employment rate : Self-employment is defined as the employment of employers, workers who work for themselves, members of producers’ co-operatives, and unpaid family workers. The latter are unpaid in the sense that they lack a formal contract to receive a fixed amount of income at regular intervals, but they share in the income generated by the enterprise. Unpaid family workers are particularly important in farming and retail trade. All persons who work in corporate enterprises, including company directors, are considered to be employees. Self-employment may be seen either as a survival strategy for those who cannot find any other means of earning an income or as evidence of entrepreneurial spirit and a desire to be one’s own boss. Employed people are as those aged 15 or over who report that they have worked in gainful employment for at least one hour in the previous week or who had a job but were absent from work during the reference week. This indicator is measured as a percentage of the employed population considered (total, men or women).

📌 Hours worked : Average annual hours worked is defined as the total number of hours actually worked per year divided by the average number of people in employment per year. Actual hours worked include regular work hours of full-time, part-time and part-year workers, paid and unpaid overtime, hours worked in additional jobs, and exclude time not worked because of public holidays, annual paid leave, own illness, injury and temporary disability, maternity leave, parental leave, schooling or training, slack work for technical or economic reasons, strike or labour dispute, bad weather, compensation leave and other reasons. The data cover employees and self-employed workers. This indicator is measured in terms of hours per worker per year. The data are published with the following health warning: The data are intended for comparisons of trends over time; they are unsuitable for comparisons of the level of average annual hours of work for a given year, because of differences in their sources and method of calculation.

Return to the tabbed sections to see more by clicking here 👉 Overview!

Return to the tabbed sections to see more by clicking here 👉 Overview!

2.3 Productivity

Productivity 📅

The data set from OECD that I am gonna use to illustrate productivity metric is the following together with its description (citation provided on references): GDP per Hour Worked

📌 GDP per hour worked : GDP per hour worked is a measure of labour productivity. It measures how efficiently labour input is combined with other factors of production and used in the production process. Labour input is defined as total hours worked of all persons engaged in production. Labour productivity only partially reflects the productivity of labour in terms of the personal capacities of workers or the intensity of their effort. The ratio between the output measure and the labour input depends to a large degree on the presence and/or use of other inputs (e.g. capital, intermediate inputs, technical, organisational and efficiency change, economies of scale). This indicator is measured in USD (constant prices 2010 and PPPs) and indices.

Return to the tabbed sections to see more by clicking here 👉 Overview!

Return to the tabbed sections to see more by clicking here 👉 Overview!

2.4 Wages

Wages 💶

The data set from OECD that I am gonna use to illustrate wage metric is the following together with its description (citation provided on references): Average Wages

📌 Average wages : Average wages are obtained by dividing the national-accounts-based total wage bill by the average number of employees in the total economy, which is then multiplied by the ratio of the average usual weekly hours per full-time employee to the average usually weekly hours for all employees. This indicator is measured in USD constant prices using 2016 base year and Purchasing Power Parities (PPPs) for private consumption of the same year.

Key Insight

According to the OECD available data, the average wage for Greece peaked at ~33.974 US Dollars in 2009. The latest available data of 2020 show an average wage of ~27.207 US Dollars, a decrease of 19.9% in the national wage average, from its peak in the last 30 years where OECD provides data for the respecting category.

From the Countries we are exploring, this is the most considerable decrease in the national average wage, with the second place in most significant decrease going to Spain with a national average wage decrease of 9.45%, from a peak of 41.883 in 2009 to 37.922 USD in 2020. Italy seems to come third with a decrease of 8.3%. Almost all of the other Countries considered have not seen a decrease in their national average wage from their respective peak. Still, their national average wages are increasing steadily over the years, with most of these countries reaching their peak during 2020, where our data information ends. This is also the case for Hungary and Slovakia. While the data from 2020 shows them to have a lower national average wage than Greece, their average wages are steadily increasing over the years.

Return to the tabbed sections to see more by clicking here 👉 Overview!

Return to the tabbed sections to see more by clicking here 👉 Overview!

2.5 Population - Demography

Population - Demography 🧍

The 3 (three) different data sets from OECD that I am gonna use to illustrate population metrics are the following together with their description (citation provided on references): Young Population , Old-age dependency ratio and Fertility Rates

📌 Young Population : The youth population is defined as those people aged less than15. The share of the dependent population is calculated as total elderly and youth population expressed as a ratio of the total population. The youth-dependency ratio relates the number of young persons that are likely to be dependent on the support of others for their daily needs to the number of those who are capable of providing such support. Demographic trends have a number of implications for government and private spending on pensions, health care, and education, and, more generally, for economic growth and welfare. This indicator is measured as a percentage of population.

📌 Old-age dependency ratio : The old-age to working-age demographic ratio is defined as the number of individuals aged 65 and over per 100 people of working age defined as those at ages 20 to 64. The evolution of old-age to working-age ratios depends on mortality rates, fertility rates and migration. OECD countries have seen prolonged increases in life expectancy that most analysts project to continue, implying an increasing number of older people and most likely of pensioners too. This indicator is meausured as a percentage.

📌 Fertility rates : The total fertility rate in a specific year is defined as the total number of children that would be born to each woman if she were to live to the end of her child-bearing years and give birth to children in alignment with the prevailing age-specific fertility rates. It is calculated by totalling the age-specific fertility rates as defined over five-year intervals. Assuming no net migration and unchanged mortality, a total fertility rate of 2.1 children per woman ensures a broadly stable population. Together with mortality and migration, fertility is an element of population growth, reflecting both the causes and effects of economic and social developments. The reasons for the dramatic decline in birth rates during the past few decades include postponed family formation and child-bearing and a decrease in desired family sizes. This indicator is measured in children per woman.

Return to the tabbed sections to see more by clicking here 👉 Overview!

Return to the tabbed sections to see more by clicking here 👉 Overview!

2.6 GDP - Debt

GDP - Debt 💰

The 2 (two) different data sets from OECD that I am gonna use to illustrate population metrics are the following together with their description (citation provided on references): Gross Domestic Product (GDP) and General Government Debt

📌 Gross Domestic Product (GDP) : Gross domestic product (GDP) is the standard measure of the value added created through the production of goods and services in a country during a certain period. As such, it also measures the income earned from that production, or the total amount spent on final goods and services (less imports). While GDP is the single most important indicator to capture economic activity, it falls short of providing a suitable measure of people’s material well-being for which alternative indicators may be more appropriate. This indicator is based on nominal GDP (also called GDP at current prices or GDP in value) and is available in different measures: US dollars and US dollars per capita (current PPPs). All OECD countries compile their data according to the 2008 System of National Accounts (SNA). This indicator is less suited for comparisons over time, as developments are not only caused by real growth, but also by changes in prices and PPPs.

📌 General Government Debt : General government debt-to-GDP ratio measures the gross debt of the general government as a percentage of GDP. It is a key indicator for the sustainability of government finance. Debt is calculated as the sum of the following liability categories (as applicable): currency and deposits; debt securities, loans; insurance, pensions and standardized guarantee schemes, and other accounts payable. Changes in government debt over time primarily reflect the impact of past government deficits.

Return to the tabbed sections to see more by clicking here 👉 Overview!

Return to the tabbed sections to see more by clicking here 👉 Overview!

3 Summary

Summary - Key Country Metrics
An overview of Country OECD data for the year 2020
Country Unemployment Rate,
ratio in %
Long-term Unemployment,
ratio in %
1
Average Wage,
in USD
Hours Worked,
Annual Hrs
GDP/hour worked,
in USD
GDP,
USD per capita
Australia 6.46% 0.00% $55.21K 1683.0 $55.80 $55.63K
Austria 6.03% 24.53% $53.13K 1400.0 $69.76 $55.69K
Belgium 5.54% 41.64% $54.33K 1481.0 $74.49 $53.09K
Canada 9.56% 5.14% $55.34K 1644.0 $56.86 $46.61K
Switzerland 4.82% 34.63% $64.82K 1495.0 $75.75 $71.69K
Czechia 2.55% 22.26% $29.88K 1705.0 $42.45 $41.60K
Germany 3.83% 0.00% $53.75K 1331.7 $66.94 $54.84K
Denmark 5.65% 16.73% $58.43K 1346.0 $75.41 $60.24K
Spain 15.53% 32.11% $37.92K 1577.2 $52.25 $37.76K
Estonia 6.88% 17.20% $30.72K 1654.0 $41.76 $37.66K
Finland 7.72% 15.90% $46.23K 1531.0 $61.27 $50.51K
France 8.03% 36.75% $45.58K 1402.0 $67.60 $46.69K
United Kingdom 4.55% 20.12% $47.15K 1367.0 $61.27 $46.58K
Greece 16.44% 66.51% $27.21K 1728.0 $34.26 $27.90K
Hungary 4.12% 27.21% $25.41K 1660.3 $39.28 $33.08K
Ireland 5.85% 24.02% $49.47K 1746.0 $111.84 $93.45K
Italy 9.30% 52.40% $37.77K 1558.7 $54.84 $41.91K
Lithuania 8.52% 28.97% $31.81K 1595.0 $44.61 $38.88K
Luxembourg 6.69% 25.54% $65.85K 1427.0 $100.86 $117.72K
Latvia 8.10% 27.33% $29.88K 1577.0 $38.79 $31.48K
Netherlands 4.85% 23.97% $58.83K 1399.0 $66.99 $59.27K
Norway 4.60% 20.94% $55.78K 1368.7 $83.18 $62.65K
Poland 3.16% 20.02% $32.53K 1766.0 $41.03 $33.88K
Portugal 7.12% 33.45% $28.41K 1613.0 $40.01 $34.18K
Slovakia 6.70% 44.97% $23.62K 1572.0 $46.08 $31.35K
Slovenia 5.01% 38.79% $41.45K 1514.6 $45.70 $39.72K
Sweden 8.29% 11.70% $47.02K 1424.0 $70.53 $55.04K
United States 8.09% 5.62% $69.39K 1767.0 $73.37 $63.29K
OECD org 2020 Data

1 Grey fields for data that are not updated from OECD.org for 2020

4 Conclusion

Home that our feet may leave, but not our hearts. — Oliver Wendell Holmes

On a personal note, from my own experiences and knowledge, the opportunities (limited to none) and the working conditions that exist in Greece are very much indicative of what one would expect from a country with these metrics.

Growing up as a child, you think that you have to follow the natural flow of the societal norm and rules. Go to school, go to university and then find a job. Easy, right? This is not the case for many young people in Greece, though, as they would be naive to think that. After they are done with their studies, they have to face a deep cultivated and crisis-enforced environment of nepotism, further amplified by unemployment and stagflation.

However, to return to the point, raw data do not always draw the complete picture of a situation, but a lot of the time is a close imitation of reality.

This reality leads many people, particularly young people, to the hard decision of leaving home and, in this case, their home country. The conditions are always different and unique for each individual. The feeling, is always the same.

You may feel like home is the anchor in your storm, but leaving may well save you from drowning.

Summary Greece & Average 2020
An overview of OECD 2020 data
Greece Average1
Unemployment Rate 14.82% 6.71%
Unemployment Rate for Tertiary Education Level 11.52% 4.17%
Long-term Unemployment Rate 66.51% 27.63%
Employment Rate 53.67% 70.17%
Self-Employment Rate 31.86% 14.18%
Hours Worked 1 728.00 1 547.61
GDP per hour worked $34.26 $60.46
Average Wage $27.21K $44.89K
GDP $27.90K $50.80K
OECD org 2020 Data

1 Countries included for the calculation of the average are the ones used for the whole analysis

Thank you for reading

End 🏁

References 📚

OECD (2022), Unemployment rate (indicator). doi: 10.1787/52570002-en (Accessed on 15 February 2022)

OECD (2022), Unemployment rate by age group (indicator). doi: 10.1787/997c8750-en (Accessed on 15 February 2022)

OECD (2022), Unemployment rates by education level (indicator). doi: 10.1787/6183d527-en (Accessed on 15 February 2022)

OECD (2022), Long-term unemployment rate (indicator). doi: 10.1787/76471ad5-en (Accessed on 15 February 2022)

OECD (2022), Youth unemployment rate (indicator). doi: 10.1787/c3634df7-en (Accessed on 15 February 2022)

OECD (2022), Employment rate (indicator). doi: 10.1787/1de68a9b-en (Accessed on 15 February 2022)

OECD (2022), Employment rate by age group (indicator). doi: 10.1787/084f32c7-en (Accessed on 15 February 2022)

OECD (2022), Employment by education level (indicator). doi: 10.1787/26f676c7-en (Accessed on 15 February 2022)

OECD (2022), Self-employment rate (indicator). doi: 10.1787/fb58715e-en (Accessed on 15 February 2022)

OECD (2022), Hours worked (indicator). doi: 10.1787/47be1c78-en (Accessed on 15 February 2022)

OECD (2022), GDP per hour worked (indicator). doi: 10.1787/1439e590-en (Accessed 15 08 February 2022)

OECD (2022), Average wages (indicator). doi: 10.1787/cc3e1387-en (Accessed on 15 February 2022)

OECD (2022), Young population (indicator). doi: 10.1787/3d774f19-en (Accessed on 15 February 2022)

OECD (2022), Old-age dependency ratio (indicator). doi: 10.1787/e0255c98-en (Accessed on 15 February 2022)

OECD (2022), Fertility rates (indicator). doi: 10.1787/8272fb01-en (Accessed on 15 February 2022)

OECD (2022), Gross domestic product (GDP) (indicator). doi: 10.1787/dc2f7aec-en (Accessed on 15 February 2022)

OECD (2022), Education spending (indicator). doi: 10.1787/ca274bac-en (Accessed on 15 February 2022)

OECD (2022), General government debt (indicator). doi: 10.1787/a0528cc2-en (Accessed on 15 February 2022)